This is the authors' abstract. We don't add key points for this paper.
Aging clocks use machine learning to estimate biological age as a proxy for general health state. Here, we critically examine their practical value, highlighting fundamental challenges: abstract definitions, inconsistent clinical validation, and ignored prediction uncertainty. By comparing aging clocks with expert risk scores, direct outcome predictors, and emerging large health models, we question their benefits and encourage researchers to explicitly justify clock advantage over established alternatives, ensuring truly actionable insights.
Answers are grounded in this paper and cite their sources.
No takes yet. Share an insight, caveat, or question.
Kriukov et al. (2025) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: